Cardiom Health Prediction

Heart Disease remains a leading cause of worldwide requiring early diagnosis to improve patient outcomes. This study proposes a machine- learning based on heart disease, utilizing a dataset of 270 patients with features like Age, Sex, Chestpain, Blood Pressure, Cholesterol, FBS over 120, EKG Results, Max HR, Exercise angina, ST Depression, Slope of ST, Number of vessels Fluro, Thallium, Heart Disease. In this project we mainly take a look on the dataset which we have been uploaded in this prediction project .The data set that consist of the details about the many patients. The data which are present in the dataset is the details about the patients so it is easy to analyze the disease of the peoples by their health condition , here for writing the code we import the libraries such as pandas , mathplotlib NumPy etc and then we upload the dataset to the program using csv file . Heart disease takes palce in the machine learning process in which the output of the prediction is formed by the visualization graph , in this heart disease prediction project the visualization can be done by the different types of graph such as Bar Graph , distribution plot , ROC curve , confusion matrix heatmap , stacks , scatter plot for feature analysis. By using this we come to know that 80% of patients are not having heart disease and 20% of patients are having the heart disease